Machine Learning for Networking: Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3–5, 2019, Revised Selected Papers

Author:   Selma Boumerdassi ,  Éric Renault ,  Paul Mühlethaler
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   12081
ISBN:  

9783030457778


Pages:   486
Publication Date:   20 April 2020
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Machine Learning for Networking: Second IFIP TC 6 International Conference, MLN 2019, Paris, France, December 3–5, 2019, Revised Selected Papers


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Author:   Selma Boumerdassi ,  Éric Renault ,  Paul Mühlethaler
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   12081
Weight:   0.759kg
ISBN:  

9783030457778


ISBN 10:   303045777
Pages:   486
Publication Date:   20 April 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Network Anomaly Detection using Federated Deep Autoencoding Gaussian Mixture Model.- Towards a Hierarchical Deep Learning Approach for Intrusion Detection.- Network Trafic Classifi cation using Machine Learning for Software Defined Networks.- A Comprehensive Analysis of Accuracies of Machine Learning Algorithms for Network Intrusion Detection.- Q-routing: from the algorithm to the routing protocol.- Language Model Co-occurrence Linking for Interleaved Activity Discovery.- Achieving Proportional Fairness in WiFi Networks via Bandit Convex Optimization.- Denoising Adversarial Autoencoder for Obfuscated Tra c Detection and Recovery.- Root Cause Analysis of Reduced Accessibility in 4G Networks.- Space-time pattern extraction in alarm logs for network diagnosis.- Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses.- Algorithm Selection and Model Evaluation in Application Design using Machine Learning.- GAMPAL: Anomaly Detection forInternet Backbone Tra c by Flow Prediction with LSTM-RNN.- Revealing User Behavior by Analyzing DNS Tra c.- A new approach to determine the optimal number of clusters based on the Gap statistic.- MLP4NIDS: an e cient MLP-based Network Intrusion Detection for CICIDS2017 dataset.- Random Forests with a Steepend Gini-Index Split Function and Feature Coherence Injection.- Emotion-based Adaptive Learning Systems.- Machine learning methods for anomaly detection in IoT networks, with illustrations.- DeepRoute: Herding Elephant and Mice Flows with Reinforcement Learning.- Arguments Against using the 1998 DARPA Dataset for Cloud IDS Design and Evaluation and Some Alternative.- Estimation of the Hidden Message Length in Steganography: A Deep Learning Approach.- An Adaptive Deep Learning Algorithm Based Autoencoder for Interference Channels.- A Learning Approach for Road Tra c Optimization in Urban Environments.- CSI based Indoor localization using Ensemble Neural Networks.- Bayesian Classi ersin Intrusion Detection Systems.- A Novel Approach towards Analysis of Attacker Behavior in DDoS Attacks.- Jason-RS, a Collaboration between Agents and an IoT Platform.- Scream to Survive(S2S): Intelligent System to Life-Saving in Disasters Relief.- Association Rules Algorithms for Data Mining Process Based on Multi Agent System.- Internet of Things: Security Between Challenges and Attacks.- Socially and biologically inspired computing for self-organizing communications networks. 

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